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remesh

Rebuild a 3D mesh into clean topology using voxel, sharp, smooth, or block modes and adjustable detail for modeling, repair, or optimization.

Instructions

Remesh an object to create a clean topology.

Args: object_name: Name of the mesh object to remesh. voxel_size: Voxel size for remeshing (smaller = more detail). Only used in VOXEL mode. mode: Remesh mode - VOXEL, SHARP, SMOOTH, or BLOCKS.

Returns: Dict with object name and new vertex count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoVOXEL
voxel_sizeNo
object_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.7.0
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / mode / enum
      Added value: +[
      +  "BLOCKS",
      +  "SHARP",
      +  "SMOOTH",
      +  "VOXEL"
      +]
  2. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full behavioral burden. It never says whether remeshing destructively rebuilds topology, replaces the original object, requires the object to be selected, or can fail on non-mesh inputs. The 'smaller = more detail' note on voxel_size and the return shape are the only behavioral context offered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose sentence is front-loaded and the args/returns blocks are compact and skimmable. The Returns block is somewhat redundant given an output schema exists, but nothing is excessively verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists so return values need no explanation, but for a topology-mutating tool with zero annotations the description omits the key facts an agent needs: destructive/replace-in-place behavior and input prerequisites. It is adequate but leaves meaningful gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it does: it explains object_name, clarifies that voxel_size is only used in VOXEL mode, and notes that smaller values yield more detail. The mode values merely restate the enum, but the VOXEL-only constraint is genuinely additive information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource ('Remesh an object') plus the goal ('create a clean topology'), which is clear enough to act on. It stops short of distinguishing itself from closely related siblings such as decimate_mesh, subdivide_mesh, or repair_mesh, leaving the agent to infer the difference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit guidance on when to remesh versus decimate, subdivide, or repair a mesh, nor any prerequisites (mesh object type, active object requirement). The mode enum hints at variants but the description never says which situation calls for which mode.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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